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Series GSE57563 Query DataSets for GSE57563
Status Public on Jan 07, 2015
Title Detecting differential peaks in ChIP-seq signals with ODIN
Organism Mus musculus
Experiment type Genome binding/occupancy profiling by high throughput sequencing
Summary Motivation: Detection of changes in DNA-protein interactions from ChIP-seq data is a crucial step in unraveling the regulatory networks behind biological processes. The simplest variation of this problem is the differential peak calling problem. Here one has to find genomic regions with ChIP-seq signal changes between two cellular conditions in the interaction of a protein with DNA. The great majority of peak calling methods can only analyse one ChIP-seq signal at a time and are unable to perform differential peak calling. Recently, a few approaches based on the combination of these peak callers with statistical tests for detecting differential digital expression have been proposed. However, these methods fail to detect detailed changes of protein-DNA interactions. Results: We propose ODIN; an HMM-based approach to detect and analyse differential peaks in pairs of ChIP-seq data. ODIN performs genomic signal processing, peak calling and p-value calculation in an integrated framework. We also propose an evaluation methodology to compare ODIN with competing methods. The evaluation method is based on the association of differential peaks with expression changes in the same cellular conditions. Our empirical study based on several ChIP-seq experiments from transcription factors, histone modifications and simulated data shows that ODIN outperforms considered competing methods in most scenarios.
 
Overall design H3K4me1 and PU.1 occupancy in MPP, CDP, cDC and pDC
 
Contributor(s) Allhoff M, Sere K, Chauvistre H, Lin Q, Zenke M, Costa IG
Citation(s) 25371479, 26476451
Submission date May 12, 2014
Last update date Mar 19, 2019
Contact name Martin Zenke
E-mail Martin.Zenke@rwth-aachen.de
Phone +49-241-80 80760
Organization name Institute for Biomedical Engineering
Department Cell Biology
Street address Universitatsklinikum Aachen, RWTH
City Aachen
State/province NRW
ZIP/Postal code 52074
Country Germany
 
Platforms (1)
GPL13112 Illumina HiSeq 2000 (Mus musculus)
Samples (8)
GSM1384935 MPP_H3K4me1
GSM1384936 CDP_H3K4me1
GSM1384937 cDC_H3K4me1
Relations
BioProject PRJNA246724
SRA SRP041893

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE57563_RAW.tar 1.0 Gb (http)(custom) TAR (of WIG)
Raw data are available in SRA
Processed data provided as supplementary file

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